Blar i NTNU Open på forfatter "Gros, Sebastien"
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Machine Learning Based Digital Twins for Temperature and Power Dynamics of a Household
Belsvik, Jacob Benedict Lindheim (Master thesis, 2023)Utfordringer med kraftproduksjonen i Europa og den stadig økende elektrifiseringen av samfunnet har resultert i økte kostnader ved strømforbruk de siste par årene. Dette har stor innvirkning på økonomien til husholdninger ... -
Model based control of water flow and level in a river system with hydropwer plant
Kalicki, Dawid (Master thesis, 2022)Enkle regulatorer som en PI-regulator er ofte brukt i implementasjon av vannstandsregulering på elvekraftverk. Slike enkle regulatorer kan være vanskelig å bruke til å implementere mer avanserte regulator funksjoner. I ... -
Model Based Parameter Estimations of Heat Pumps and Heat Dynamics of a Household
Nesje, Andreas Tveita (Master thesis, 2021)Studier viser at samfunnet må tilpasse seg overgangen knyttet til økt elektrifisering og fornybar energi til energimiksen. Kombinasjonen av høyere strømforbruk og ikke-regulerbare energikilder vil føre til høyere variasjon ... -
Model Predictive Control for Lateral Path Tracking of an Autonomous Formula Student Race Car
Borg, Christine Sääv (Master thesis, 2020)I flere tiår har Formula Student vært en velletablert ingeniørkonkurranse for studenter over hele verden. Konkurransen har i hovedsak vært arrangert for å teste studentenes kunnskap og evner innenfor det mekaniske og ... -
Model-based Reinforcement Learning for Variable Impedance Control
Anand, Akhil Sadanandan (Doctoral theses at NTNU;2023:149, Doctoral thesis, 2023)This thesis is a collection of research work in the area of reinforcement learning and robotic manipulation. A set of new results on reinforcement learning focusing on model-based approaches and variable impedance control ... -
MPC based approach for peak load reduction in smart homes
Westad Larssen, Mathias (Master thesis, 2022)Når samfunnet stadig elektrifiserer flere nøkkelindustrier og transportsektoren for å redusere klimautslippet, er det viktigere enn noen gang at samfun- net har investert i kraftnettet og at det brukes effektivt. At ... -
A Nonlinear State Observer for the Bi-Hormonal Intraperitoneal Artificial Pancreas
Davari Benam, Karim; Khoshamadi, Hasti; Lema-Pérez, Laura; Gros, Sebastien; Fougner, Anders Lyngvi (Chapter, 2022)Currently, continuous glucose monitoring sensors are used in the artificial pancreas to monitor blood glucose levels. However, insulin and glucagon concentrations in different parts of the body cannot be measured in ... -
Optimal Design and Usage of Battery Storage in Private Houses Using Optimal Control and Stochastic MPC
Haugann, Håkon (Master thesis, 2022)Denne masteroppgaven er en del av POWIOT-prosjektet, som tar sikte på å lage et Internet of Things (IoT) basert strømstyringssystem for å minimere strømkostnader i smarte bygg og for å utjevne belastningen på strømnettet. ... -
Optimal Model-Based Trajectory Planning With Static Polygonal Constraints
Martinsen, Andreas Bell; Lekkas, Anastasios; Gros, Sebastien (Peer reviewed; Journal article, 2021)The main contribution of this article is a novel method for planning globally optimal trajectories for dynamical systems subject to polygonal constraints. The proposed method is a hybrid trajectory planning approach, which ... -
Optimization-Based Automatic Docking and Berthing of ASVs Using Exteroceptive Sensors: Theory and Experiments
Martinsen, Andreas Bell; Bitar, Glenn Ivan; Lekkas, Anastasios M.; Gros, Sebastien (Peer reviewed; Journal article, 2020)Docking of autonomous surface vehicles (ASVs) involves intricate maneuvering at low speeds under the influence of unknown environmental forces, and is often a challenging operation even for experienced helmsmen. In this ... -
Parametrisk usikkerhet i modellbasert regulering
Sæle, Ludvig Stangeland (Master thesis, 2019)Denne oppgaven tar i betraktning arbeidet utført på APT-simulatoren som Hans Erik Frøyen startet på i sin masteroppgave. Nicolay Erlbeck og Karl Arthur Unstad videreutviklet denne simulatoren i sine oppgaver. Oppgaven ... -
Precision Deep-Stall Landing of Fixed-Wing UAVs using Nonlinear Model Predictive Control
Mathisen, Siri Gulaker; Gros, Sebastien; Johansen, Tor Arne (Peer reviewed; Journal article, 2020)To be able to recover a fixed-wing unmanned aerial vehicle (UAV) on a small space like a boat deck or a glade in the forest, a steep and precise descent is needed. One way to reduce the speed of the UAV during landing is ... -
Rare event chance-constrained optimal control using polynomial chaos and subset simulation
Piprek, Patrick; Gros, Sebastien; Holzapfel, Florian (Journal article; Peer reviewed, 2019)This study develops a chance–constrained open–loop optimal control (CC–OC) framework capable of handling rare event probabilities. Therefore, the framework uses the generalized polynomial chaos (gPC) method to calculate ... -
Recursive Feasibility of Stochastic Model Predictive Control with Mission-Wide Probabilistic Constraints
Wang, Kai; Gros, Sebastien (Chapter, 2021)This paper is concerned with solving chance-constrained finite-horizon optimal control problems, with a particular focus on the recursive feasibility issue of stochastic model predictive control (SMPC) in terms of mission-wide ... -
Reinforcement learning-based NMPC for tracking control of ASVs: Theory and experiments
Martinsen, Andreas Bell; Lekkas, Anastasios; Gros, Sebastien (Peer reviewed; Journal article, 2022)We present a reinforcement learning-based (RL) model predictive control (MPC) method for trajectory tracking of surface vessels. The proposed method uses an MPC controller in order to perform both trajectory tracking and ... -
Reinforcement Learning-Based Tracking Control of USVs in Varying Operational Conditions
Martinsen, Andreas Bell; Lekkas, Anastasios M.; Gros, Sebastien (Peer reviewed; Journal article, 2020)We present a reinforcement learning-based (RL) control scheme for trajectory tracking of fully-actuated surface vessels. The proposed method learns online both a model-based feedforward controller, as well an optimizing ... -
Risk-Based Model Predictive Control for Autonomous Ship Emergency Management
Blindheim, Simon; Gros, Sebastien; Johansen, Tor Arne (Peer reviewed; Journal article, 2020)Control for semi- and fully-autonomous ships is a broad and complex field. Making autonomous high-level decisions in place of the captain is considered difficult, partly due to the risks and uncertainties involved. Though ... -
Safe Reinforcement Learning using Model Predictive Control: An analysis of utilising anisotropic exploration with deterministic policy gradients
Frekhaug, Thomas Aleksander (Master thesis, 2020)Denne avhandlingen er en studie i Trygg Forsterkende Læring (eng: Reinforcement Learning, RL) der det blir benyttet utforskningsagenter (eng: policy) som bruker anisotropisk utforskning. Trygg RL er en ny kategori av RL ... -
Safe Reinforcement Learning Using Wasserstein Distributionally Robust MPC and Chance Constraint
Bahari Kordabad, Arash; Wisniewski, Rafael; Gros, Sebastien (Peer reviewed; Journal article, 2022)In this paper, we address the chance-constrained safe Reinforcement Learning (RL) problem using the function approximators based on Stochastic Model Predictive Control (SMPC) and Distributionally Robust Model Predictive ... -
Subspace Predictive Control for Smart Home Optimization
Husby, Oliver Kristiansen (Master thesis, 2023)I løpet av det siste året har strømprisene skutt i været og blitt en mye større økonomisk byrde for mange enn den har vært tidligere. På grunn av dette, begynte den norske regjeringen i slutten av 2021 å subsidiere borgerne ...